A hybrid regression model for water quality prediction

Abstract

In this work, we propose a hybrid regression model to solve a specific problem faced by a modern paper manufacturing company. Boiler inlet water quality is a major concern for the paper machine. If water treatment plant can not produce water of desired quality, then it results in poor health of the boiler water tube and consequently affects the quality of the paper. This variation is due to several crucial process parameters. We build a hybrid regression model based on regression tree and support vector regression for boiler water quality prediction and show its excellent performance as compared to other state-of-the-art.

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Acknowledgements

The authors acknowledge the concerned editor and reviewers for their constructive comments.

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Correspondence to Tanujit Chakraborty.

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Chakraborty, T., Chakraborty, A.K. & Mansoor, Z. A hybrid regression model for water quality prediction. OPSEARCH 56, 1167–1178 (2019). https://doi.org/10.1007/s12597-019-00386-z

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Keywords

  • Water quality
  • Decision tree
  • Support vector regression
  • Hybrid model